Cellular telephone and data network operators currently suffer revenue leakage from existing services and networks for a variety of reasons. Additionally, new service demands, integration of new technology and platforms, requirements for real-time processing, and dependence upon third parties for content and billing are increasing network operators' exposure to revenue leakage. Ensuring the completeness and accuracy of transactions processed, and the application of correct tariffs and policies, is now a much more complex challenge for network operators.
Revenue assurance represents both a large opportunity for network operators to maximize their reported (and billed) revenues, and an opportunity to identify and reduce unnecessary revenue leakage that can arise. Reports estimate that telecoms network operators incur average revenue per user (ARPU) losses of between 10% and 15% as a result of weak revenue assurance practices. These losses are typically related to issues with accuracy and completeness of information flowing through various systems in the revenue stream, such as provisioning, usage processing and billing. For network operators and content providers, revenue assurance also plays a large role in identifying revenue losses caused by the failure of content delivery networks or the operators' systems to deliver content to users' devices in an accurate and timely manner.
Recently enacted legal and regulatory requirements, such as the Sarbanes-Oxley Act in the United States, compel corporate officers to certify that they have established and continue to maintain internal controls for assuring the accuracy of corporate financial reports. These requirements have further driven activity in, and the importance attached to, revenue assurance outside the traditional finance, product and marketing related functions. For example, in the event of a revenue related issue emerging for a network operator, the directors can use their implementation of best in class revenue assurance systems as a defense.
Network operators' revenue models are highly complex, and this complexity continues to grow—with many users consuming different services, on different price plans, using different devices. A single user may also pay for these services in various ways, such as via a traditional post-paid invoice, on a pre-paid basis, or with some combination of the pre-paid and post-paid arrangements, depending on the specific service or content being consumed. More recently, the introduction of “sponsored data” services in which a content provider or another third-party pays for a user's consumption of a service, has added yet another layer of complexity to revenue assurance systems.
Traditionally, revenue assurance systems have had to rely on trend analysis tools and sampling and statistical validations in order to address the challenges of completeness and accuracy. However, services offered to users were not typically charged and consumed in real time—i.e., the rating and charging functions were performed post-event, usually in batch mode. The advent of prepaid services, and more recently shared monetary and non-monetary balances across multiple services, devices and users, as well as services and content that can be paid for on an ad hoc basis, have brought about a change of emphasis in the rating and charging of network usage records. To date real-time tariffs and the options available to users have been relatively simple and non-complex propositions (largely due to the technology and business models still evolving).
The growth of IP-based services has further compounded the difficulties associated with providing network operators with an adequate revenue assurance solution. IP network nodes typically generate an order of magnitude more usage records compared with usage records for circuit-switched networks. In addition, IP usage records can arrive out of sequence because they are not ordered or hierarchical; are often incomplete due to, for example, incorrectly terminated, long lasting sessions or lost packets; and are typically more complex and disparate than non-IP based usage records. For example, a mobile phone call might generate five usage records (i.e., CDRs) with the same phone number. On the other hand, an IP session may generate hundreds of URL usage records with multiple different IP addresses that need to be correlated, and which need to be related to an access point and associated with a user's mobile device. Since these relationships are typically recorded in an authentication record (e.g., an AAA record), it is often challenging to validate, aggregate, and correlate users' usage records completely and accurately in real-time for both the network operator and third-party provided services. Further, as noted above, these records may represent different content and services consumed by the user, and each service may have to be charged differently based on the defined business rules, user subscriptions, etc. For all the forgoing reasons, providing adequate revenue assurance systems in IP-based networks involves challenging design criteria that must be satisfied by network operators and system engineers.
Looking forward, two things are expected to change that will make the challenges associated with providing network operators with adequate revenue assurance systems even more pronounced. Firstly, network operators and their partners are expected to offer their users increasing quantities and varieties of services. Secondly, network operators are expected to offer their users more sophisticated real-time environments and user propositions (e.g., mobile videoconferencing, mobile TV, etc.). Many of these complex services are delivered via a plurality of network elements, each of which may have different service monitoring and usage reporting capabilities, making reconciliation of usage reports from across these elements all the more challenging. As a result, revenue leakage in real-time rating and charging functions/systems may mean real-time losses for network operators and potentially even their partners.
The challenges presented by these expected changes are further compounded by recent and anticipated legal and regulatory changes (e.g., Sarbanes-Oxley) that may require network operators to maintain more formal evidence that adequate checks and tests have been conducted by accounting and billing systems. Consequently, network operators may also be compelled to put in place adequate and sufficient systems to provide more effective, robust, and efficient revenue assurance systems and solutions.